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Characterizing barren plateaus in quantum ansätze with the adjoint representation.

Enrico FontanaDylan HermanShouvanik ChakrabartiNiraj KumarRomina YalovetzkyJamie HeredgeShree Hari SureshbabuMarco Pistoia
Published in: Nature communications (2024)
Variational quantum algorithms, a popular heuristic for near-term quantum computers, utilize parameterized quantum circuits which naturally express Lie groups. It has been postulated that many properties of variational quantum algorithms can be understood by studying their corresponding groups, chief among them the presence of vanishing gradients or barren plateaus, but a theoretical derivation has been lacking. Using tools from the representation theory of compact Lie groups, we formulate a theory of barren plateaus for parameterized quantum circuits whose observables lie in their dynamical Lie algebra, covering a large variety of commonly used ansätze such as the Hamiltonian Variational Ansatz, Quantum Alternating Operator Ansatz, and many equivariant quantum neural networks. Our theory provides, for the first time, the ability to compute the exact variance of the gradient of the cost function of the quantum compound ansatz, under mixing conditions that we prove are commonplace.
Keyphrases
  • molecular dynamics
  • energy transfer
  • density functional theory
  • monte carlo
  • machine learning
  • neural network